1. Field of Invention
This invention relates to mobile communications field, and more particularly, to a scheduling method using imperfect CQI (Channel Quality Information) feedback and a scheduler using the scheduling method, especially for WiMAX.
2. Description of Prior Art
IEEE 802.16, also known as WiMAX, has emerged as a strong candidate standard for the future wireless systems, primarily because it offers the potentials for high spectral efficiency, flexible spectrum options, and scalable carrier bandwidth options, as well as the most promising feature, mobility. To achieve above goals, is the WiMAX physical layer (PHY) is based on OFDM (Orthogonal Frequency Division Multiplexing), a scheme that offers good resistance to multi-path and allows WiMAX to operate in NLOS (Non Line Of Sight) conditions. The OFDM technology is also widely recognized as the PHY method for the next generation communications, like 3G LTE (Long Term Evolution). WiMAX's high spectral efficiency is also obtained by using high order modulation and error correction coding scheme under very good signal conditions.
In WiMAX, the whole spectrum is divided into many sub-carriers, and a frame includes many symbols. The combination of carriers and symbols is the radio resource which could be allocated to MS for data transmission. To track the wireless channel, a pilot signal is inserted into sub-carriers every symbol. The channel quality could be estimated by the received pilot signal.
FIG. 1 is a schematic diagram showing a typical WiMAX network scenario.
For example, in a typical mobile WiMAX system shown in FIG. 1, the mobile station (MS) 41, 42, 43 or 44 sends or receives data to or from the base station (BS) 31 or 32 through its wireless interface. The WiMAX BSs 31 and 32 are connected to the internet 10 through a gateway 20.
In a Cell 1, there are lots of MSs (41, 42 and 43). Some are static users (static user 41), some are moving slowly (pedestrian user 42) while communicating with others through their WiMAX handsets, and some are using handsets on vehicles (vehicular users 43). However, due to multi-path fading and mobility, the wireless channel is not stable with the time. It is changing from time to time. Deep fading can cause one user's data transmission failed. This wastes the wireless bandwidth. To solve the problem, the proportional fairness scheduling algorithm is proposed. The BS scheduler always picks the user who has the best channel quality for data transmission. This is also known as the multi-user diversity. For example, in FIG. 1, each MS 41, 42, 43 or 44 reports its channel quality information (CQI) to the BS 31 or 32 periodically. A packet scheduler in the BS 31 or 32 decides data of which MS 41, 42, 43 or 44 to be transmitted in the next frame based on the MSs' CQI.
Basically, there are two problems that the BS packet scheduler should solve: to increase the spectrum efficiency (also known as the cell throughput) and to guarantee the fairness among multiple MSs.
On the one hand, the goal of the BS packet scheduler is to allocate the radio resource (sub-carriers and symbols in a frame) to an appropriate MS among multiple MSs whose channel conditions are various. For example, when an MS's channel is in a good condition, allocation of resource to such station would gain good spectrum efficiency and a high cell throughput. But if the BS allocates resource to an MS whose channel condition is bad, the spectrum efficiency and cell throughput are low. This problem should be solved by the BS packet scheduler.
On the other hand, if all the resource is allocated to the MSs whose channel conditions are good, the throughput would be very low for the MSs whose channel conditions are bad. In this case, the fairness among multiple MSs is deteriorated. The BS packet scheduler should also handle such a problem.
To solve the problems, a proportional fairness (PF) scheduling algorithm is first proposed in Reference [1]. Then it is adopted as the default working scheduling algorithm in IEEE 802.16m (cf. Reference [2]).
FIG. 2 is a flowchart showing the PF scheduling process.
Referring to FIG. 2, first, each MS collects the CQI status during a frame length. The value could be measured through pilot signal or data signal. Then it feedbacks the information to the BS through a dedicated logical channel (specified time and frequency) or data channel (S201). When the BS collects each MS's CQI information in the last frame, it first utilizes a link adaptation algorithm to get each MS's instantaneous transmission rate (S203). Then a PF scheduling algorithm is applied which picks the user for data transmission in the next frame (S205).
The key idea of the PF scheduling algorithm can be described as:                The user with the highest metric        
  M  =            max      i        ⁢          (              M        i            )      out of all N users will receive transmission opportunity in the next frame (S207).
                              M          i                =                              R            i            current                                R            i            history                                              (        1        )                             where Ricurrent is the user i's instantaneous rate at the scheduling moment. It is decided by the feedback CQI according to a CQI-Rate mapping table in the link adaptation module. Rihistory is the user i′s history throughput.        
According to the PF scheduling algorithm, when two users have the same history throughput, the one with higher instantaneous rate (high CQI) would get the transmission opportunity in the next frame, which increases the system throughput (spectrum efficiency). When the two users have the same instantaneous rate, the one with the lower history average rate (throughput) will transmit its data in the next frame, which guarantees the fairness between users. So, a PF scheduler could solve the problem listed above.
Reference [3] provides a PF scheduling method for high speed downlink packet access (HSDPA) system. At the scheduling time point, the BS queries each user's transmission block size to decide the user's current transmission rate Ricurrent in Equation (1).
Reference [4] applies a PF scheduling algorithm into a wireless network with relay stations. The PF scheduling part is the same as the existing solution (Reference [1]).
Reference [5] is the same as the traditional PF scheduling algorithm, except that it uses BLER (Block Error Rate) to correct the scheduling metric. It assumes the measured feedback CQI information is reliable, however, in a high mobility scenario, it is not true. So the unreliable CQI could lead to a bad system performance.
The algorithms in the prior arts all assume that the feedback CQI is reliable. This is true for static users (low mobility) in the most cases, but does not hold for mobile users. When the MS is moving, the channel Doppler spread effect results in the quick channel condition variation. When the channel degrades to a bad condition, the transmitted packet is lost. The Doppler effect is proportional to the speed of the mobile station. This means that at higher moving speeds, the channel changes more quickly, and it is more difficult for the receiver to track it. In such a case, the reported CQI of the fast moving MS is not as reliable as the low mobility MS. So the packet scheduling algorithm based on the reported CQI would cause the system throughput deteriorated.
Although the short CQI report interval could alleviate such a problem in some extent, however, for WiMAX system, the 5 ms report duration makes the Doppler effect obvious. On the other hand, a shorter frame length could not solve the problem when the MS is moving fast.
FIGS. 3A and 3B show the channel changing (BER performance and SNR performance) with time for vehicular users moving at a speed of 120 km/h. For WiMAX system, the minimum scheduling interval is a frame duration which includes 50 symbols time. The received SNR is the feedback CQI. FIG. 3B shows the CQI changes within 2 frames. Due to Doppler spread which is proportional to the user's moving speed, the channel is changing quickly. The low CQI value will lead to BER (Bit Error Rate) rising as shown in FIG. 3A. From the plots as shown in FIGS. 3A and 3B, we could see that the high/low CQI in the last frame does not definitely mean high/low in the next frame when the MS is moving. Scheduling algorithms such as the ones in the prior arts which are based on this unreliable CQI would lead to a bad cell throughput performance.